[C <scp>ii</scp>] 158 μm emission as an indicator of galaxy star formation rate
Bibliographic record
Abstract
ABSTRACT Observations of local star-forming galaxies (SFGs) show a tight correlation between their singly ionized carbon line luminosity ($L_{\rm [C\, {\small II}]}$) and star formation rate (SFR), suggesting that $L_{\rm [C\, {\small II}]}$ may be a useful SFR tracer for galaxies. Some other galaxy populations, however, are found to have lower $L_{\rm [C\, {\small II}]}{}/{}\rm SFR$ than local SFGs, including the infrared (IR)-luminous, starburst galaxies at low and high redshifts as well as some moderately SFGs at the epoch of re-ionization (EoR). The origins of this ‘$\rm [C\, {\small II}]$ deficit’ is unclear. In this work, we study the $L_{\rm [C\, {\small II}]}$–SFR relation of galaxies using a sample of z = 0–8 galaxies with $M_*\approx 10^7-5\times 10^{11}\, \mathrm{M}_\odot$ extracted from cosmological volume and zoom-in simulations from the Feedback in Realistic Environments (fire) project. We find a simple analytic expression for $L_{\rm [C\, {\small II}]}$/SFR of galaxies in terms of the following parameters: mass fraction of $\rm [C\, {\small II}]$-emitting gas ($f_{\rm [C\, {\small II}]}$), gas metallicity (Zgas), gas density (ngas), and gas depletion time ($t_{\rm dep}{}={}M_{\rm gas}{}/{}\rm SFR$). We find two distinct physical regimes: $\rm H_2$-rich galaxies, where tdep is the main driver of the $\rm [C\, {\small II}]$ deficit and $\rm H_2$-poor galaxies where Zgas is the main driver. The observed $\rm [C\, {\small II}]$ deficit of IR-luminous galaxies and early EoR galaxies, corresponding to the two different regimes, is due to short gas depletion time and low gas metallicity, respectively. Our result indicates that the $\rm [C\, {\small II}]$ deficit is a common phenomenon of galaxies, and caution needs to be taken when applying a constant $L_{\rm [C\, {\small II}]}$-to-SFR conversion factor derived from local SFGs to estimate cosmic SFR density at high redshifts and interpret data from upcoming $\rm [C\, {\small II}]$ line intensity mapping experiments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".